1. Field of the Invention
The invention relates to information retrieval systems and particularly to an adaptive meta-tagging of documents in information retrieval systems located on network servers such as found in the World Wide Web.
2. Description of Related Art
Meta-information is information about information. Some documents or files contain sections which contain meta-information related to the contents of that document or file. An example of meta-information is a keyword list. A meta-tag is an entry in a meta-information section of a document or file.
Web search services like InfoSeek and AltaVista are better at finding the correct webpages if the pages are encoded with meta-tags specifying keywords that users want to use to find the pages in question. Unfortunately, page authors are rarely capable of predicting all the search terms users want to use in searching for the information. For example, the page for a product known as “Workshop for C” would not be found by a user entering the search phrase “C compiler” unless the page author has remembered to add the term “compiler” as a keyword in a meta-tag for the page. It is empirically true that page authors often forget to do so. The need for help in meta-tagging is particularly acute due to the verbal disagreement phenomenon which is that different people often use different terms to describe the same thing. Thus, even if the page author remembers to enter meta-tagged keywords, the author may still leave out a search term used by some users because the author simply didn't think of this term.
Some search engines attempt to compensate for poor keyword tagging by the use of synonym searches. For example, the Excite search engine has a so-called concept search that is claimed to be able to find pages even if the user's query term does not appear on the page. This method has the obvious weakness that it only helps those users who use a search engine that implement synonym searches. Furthermore, the general Internet search engines have to rely on general synonym dictionaries that are not optimized for the domain of any specific website.
The Problems
Most information retrieval systems use indexing which is static, that is, once a document is indexed, its indexing doesn't change. Since language changes, it would be desirable to permit indexing to evolve in the same way.
It would be desirable to enhance the relevance of documents or files retrieved in response to search queries.